Displaying datasets 476 - 500 of 615 in total

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published: 2020-01-20
 
This datasets provide basis of our analysis in the paper - Revising the Ozone Depletion Potentials for Short-Lived Chemicals such as CF3I and CH3I. All datasets here are from the model output (CAM4-chem). All the simulations (background and perturbation) were run to steady-state and only the last year outputs used in analysis are archived here.
keywords: Illinois Data Bank; NetCDF; Ozone Depletion Potential; CF3I and CH3I
published: 2020-02-05
 
The Delt_Comb.NEX text file contains the original data used in the phylogenetic analyses of Zahniser & Dietrich, 2013 (European Journal of Taxonomy, 45: 1-211). The text file is marked up according to the standard NEXUS format commonly used by various phylogenetic analysis software packages. The file will be parsed automatically by a variety of programs that recognize NEXUS as a standard bioinformatics file format. The first nine lines of the file indicate the file type (Nexus), that 152 taxa were analyzed, that a total of 3971 characters were analyzed, the format of the data, and specification for two symbols used in the dataset. There are four datasets separated into blocks, one each for: 28S rDNA gene, Histone H3 gene, morphology, and insertion/deletion characters scored based on the alignment of the 28S rDNA dataset. Descriptions of the morphological characters and more details on the species and specimens included in the dataset are provided in the publication using this dataset. A text file, Delt_morph_char.txt, is available here that states the morphological characters and characters states that were scored in the Delt_Comb.NEX dataset. The original DNA sequence data are available from NCBI GenBank under the accession numbers indicated in publication. Chromatogram files for each sequencing read are available from the first author upon request.
keywords: phylogeny; DNA sequence; morphology; parsimony analysis; Insecta; Hemiptera; Cicadellidae; leafhopper; evolution; 28S rDNA; histone H3; bayesian analysis
published: 2020-02-01
 
This data describes habitat use, availability, landscape level influences, and daily movement of dabbling ducks in the Wabash River Valley of southeastern Illinois and southwestern Indiana. It contains triangulated locations of individual ducks, associated habitat assignments of those locations, flood survey data to determine water availability, and randomly generated points to assess landscape level questions.
keywords: waterfowl; ducks; dabbling; mallard; teal; habitat
published: 2020-01-28
 
This dataset includes two data files that provide the time series (Jul. - Sep. 2017) data of sun-induced chlorophyll fluorescence (SIF_760) collected under sunny conditions at two maize sites (one rainfed and the other irrigated) in Nebraska in 2017. Data contain 392 SIF_760 records at the rainfed site and 707 records at the irrigated site. The timestamp uses local standard time. Data are available for the sunny conditions from 8 am to 5 pm (corresponding to 9 am to 6 pm local time) throughout the study period.
keywords: sun-induced chlorophyll fluorescence (SIF); maize; gross primary production(GPP); light use efficiency(LUE); SIF yield
published: 2020-01-27
 
Morphologic data of dunes in the World's big rivers. Morphologic descriptors for large dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, dune flow depth (at the crest), and the fractional height of the maximum slope on the leeside for each dune. Morphologic descriptors for small dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, and dune flow depth (at the crest).
keywords: dune; bedform; rivers; morphology;
published: 2019-12-22
 
Dataset providing calculation of a Competition Index (CI) for Late Pleistocene carnivore guilds in Laos and Vietnam and their relationship to humans. Prey mass spectra, Prey focus masses, and prey class raw data can be used to calculate the CI following Hemmer (2004). Mass estimates were calculated for each species following Van Valkenburgh (1990). Full citations to methodological papers are included as relationships with other resources
keywords: competition; Southeast Asia; carnivores; humans
published: 2019-12-17
 
This dataset provides the raw data, code and related figures for the paper, "Channel Activation of CHSH Nonlocality"
keywords: Super-activation; Non-locality breaking channel
published: 2019-12-10
 
The dataset consists of two types of data: the estimate of land productivity (the maximum productivity, MP) and the estimate of land that has low productivity for any major crops planted in the Contiguous United States and then may be available for growing bioenergy crops (the marginal land, ML). All data items are in GeoTiff format, under the World Geodetic System (WGS) 84 project, and with a resolution of 0.0020810045 degree (~250 m). The MP values are calculated based on machine learning model estimated yields of major crops in the CONUS, and its expected value (MP_mean.tif), and associated uncertainty (MP_IDP.tif). The ML availability data have two versions: a deterministic version and a version with uncertainty. The deterministic MLs are determined as the land pixels with expected MP values falling in the range defined in the following criteria, and the MLs with uncertainty are determined as the probability that the MP value of a land pixel falls in the range defined in the following criteria: Criteria_____Description S1________ Current crop and pasture land with MP <= P50 S2________ Current crop and pasture land with MP <= P25 S3________ S1 + current grass and shrub land with P25 < MP < P50 S4________ S2 + current grass and shrub land with P10 < MP < P25 Economic__ Current crop and pasture land with potential profitability < 0 Here P10, P25 and P50 are the 10th, 25th and 50th percentile of crop MP values
keywords: Land productivity;marginal land;land use
published: 2019-12-12
 
This dataset contains gamma-ray spectra templates for a source interdiction and uranium enrichment measurement task. This dataset also contains Keras machine learning models trained using datasets created using these templates.
keywords: gamma-ray spectroscopy; neural networks; machine learning; isotope identification; uranium enrichment; sodium iodide; NaI(Tl)
published: 2019-12-03
 
This is the data set associated with the manuscript titled "Extensive host-switching of avian feather lice following the Cretaceous-Paleogene mass extinction event." Included are the gene alignments used for phylogenetic analyses and the cophylogenetic input files.
keywords: phylogenomics, cophylogenetics, feather lice, birds
published: 2019-12-03
 
These are the alignments of transcriptome data used for the analysis of members of Heteroptera. This dataset is analyzed in "Deep instability in the phylogenetic backbone of Heteroptera is only partly overcome by transcriptome-based phylogenomics" published in Insect Systematics and Diversity.
keywords: Heteroptera; Hemiptera; Phylogenomics; transcriptome
published: 2019-11-18
 
VCF files used to analyze a novel filtering tool VEF, presented in the article "VEF: a Variant Filtering tool based on Ensemble methods".
keywords: VCF files; filtering; VEF
published: 2019-10-16
 
Human annotations of randomly selected judged documents from the AP 88-89, Robust 2004, WT10g, and GOV2 TREC collections. Seven annotators were asked to read documents in their entirety and then select up to ten terms they felt best represented the main topic(s) of the document. Terms were chosen from among a set sampled from the document in question and from related documents.
keywords: TREC; information retrieval; document topicality; document description
published: 2019-11-12
 
We are sharing the tweet IDs of four social movements: #BlackLivesMatter, #WhiteLivesMatter, #AllLivesMatter, and #BlueLivesMatter movements. The tweets are collected between May 1st, 2015 and May 30, 2017. We eliminated the location to the United States and focused on extracting the original tweets, excluding the retweets. Recommended citations for the data: Rezapour, R. (2019). Data for: How do Moral Values Differ in Tweets on Social Movements?. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9614170_V1 and Rezapour, R., Ferronato, P., and Diesner, J. (2019). How do moral values differ in tweets on social movements?. In 2019 Computer Supported Cooperative Work and Social Computing Companion Publication (CSCW’19 Companion), Austin, TX.
keywords: Twitter; social movements; black lives matter; blue lives matter; all lives matter; white lives matter
published: 2019-10-18
 
Supporting secondary data used in a manuscript currently in submission regarding the invasion dynamics of the asian tiger mosquito, Aedes albopictus, in the state of Illinois
keywords: albopictus;mosquito
published: 2019-07-04
 
Software (Matlab .m files) for the article: Lying in Wait: Modeling the Control of Bacterial Infections via Antibiotic-Induced Proviruses. The files can be used to reproduce the analysis and figures in the article.
keywords: Matlab codes; antibiotic-induced dynamics
published: 2019-09-25
 
<sup>12</sup>CO and <sup>13</sup>CO maps for six molecular clouds in the Large Magellanic Cloud, obtained with the Atacama Large Millimeter/submillimeter Array (ALMA). See the associated article in the Astrophysical Journal, and README files within each ZIP archive. Please cite the article if you use these data.
keywords: Radio astronomy
published: 2019-09-17
 
Trained models for multi-task multi-dataset learning for text classification as well as sequence tagging in tweets. Classification tasks include sentiment prediction, abusive content, sarcasm, and veridictality. Sequence tagging tasks include POS, NER, Chunking, and SuperSenseTagging. Models were trained using: <a href="https://github.com/socialmediaie/SocialMediaIE/blob/master/SocialMediaIE/scripts/multitask_multidataset_classification_tagging.py">https://github.com/socialmediaie/SocialMediaIE/blob/master/SocialMediaIE/scripts/multitask_multidataset_classification_tagging.py</a> See <a href="https://github.com/socialmediaie/SocialMediaIE">https://github.com/socialmediaie/SocialMediaIE</a> and <a href="https://socialmediaie.github.io">https://socialmediaie.github.io</a> for details. If you are using this data, please also cite the related article: Shubhanshu Mishra. 2019. Multi-dataset-multi-task Neural Sequence Tagging for Information Extraction from Tweets. In Proceedings of the 30th ACM Conference on Hypertext and Social Media (HT '19). ACM, New York, NY, USA, 283-284. DOI: https://doi.org/10.1145/3342220.3344929
keywords: twitter; deep learning; machine learning; trained models; multi-task learning; multi-dataset learning; classification; sequence tagging
published: 2019-09-05
 
The data set here include data from NMR, LC-MS/MS, MALDI-MS, H/D exchange MS experiments used in paper "A novel rotifer derived alkaloid paralyzes schistosome larvae and prevents infection".
published: 2019-09-06
 
This is a dataset of 1101 comments from The New York Times (May 1, 2015-August 31, 2015) that contains a mention of the stemmed words vaccine or vaxx.
keywords: vaccine;online comments
published: 2019-08-29
 
This is the published ortholog set derived from whole genome data used for the analysis of members of the B. tabaci complex of whiteflies. It includes the concatenated alignment and individual gene alignments used for analyses (Link to publication: https://www.mdpi.com/1424-2818/11/9/151).
published: 2019-07-04
 
Results generated using SharpTNI on data collected from the 2014 Ebola outbreak in Sierra Leone.
published: 2019-07-29
 
Datasets used in the study, "TRACTION: Fast non-parametric improvement of estimated gene trees," accepted at the Workshop on Algorithms in Bioinformatics (WABI) 2019.
keywords: Gene tree correction; horizontal gene transfer; incomplete lineage sorting
published: 2019-08-15
 
Simulation data related to the paper "Mastitis risk effect on the economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study"
keywords: paratuberculosis;simulation;dairy
published: 2019-08-30
 
This dataset includes the data from an analysis of bobcat harvest data with particular focus on the relationship between catch-per-unit-effort and population size. The data relate to bobcat trapper and hunter harvest metrics from Wisconsin and include two RDS files which can be open in the software R using the readRDS() function.
keywords: bobcat; catch-per-unit-effort; CPUE; harvest; Lynx rufus; wildlife management; trapper; hunter